Prediction of Land Use Changes Using CA-Markov: A Case Study of Yasuj City

Document Type : Research Paper

Authors

1 Associate Professor, Faculty of Humanities, University of Mohaghegh Ardabili, Ardabil, Iran

2 MSc. Student, Faculty of Humanities, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract

Land use mapping and land use maps related to the prediction of spatial-temporal changes provide a major portion of the information required by urban planners and administrators to adopt correct measures and make principled decisions to achieve sustainable urban development. The purpose of this investigation was to examine land use and land cover changes in Yasuj city in the past and, consequently, to predict the spatial pattern of the land structure in the near future. In this study, the satellite object-based image analysis of the images taken by Landsat satellite in 1990, 2000, and 2018 was used to make a dynamic modeling of Yasuj lands use changes. Moreover, a combination of the Markov chain and automated cells were employed to predict land use changes. The results showed that during the period between 1991 and 2018, the area of pasturelands decreased by 7.18%, while the total area of residential areas increased by 2.02%. That is to say, the spread of Yasuj city has led to the increase in the residential and irrigated cultivation lands, while it has decreased pastures, forests, dryland cultivation areas, barren lands, and gardens. Furthermore, the development process of Yasuj city shows its tendency to physical-spatial expansion in all dimensions. Moreover, the land use map for the years 2030 and 2040 was predicted by the CA-Markov model. The results showed that during the period 2018-2040, pasturelands, dryland farming areas, and forests will decrease 1.08%, 1.03%, and 1.47%, respectively, residential areas will increase by 4.17%, and the waterbody will change a little. The results of the study show the high efficiency of the CA-Marcov model for monitoring the trend of changes, especially urban growth, for the coming years based on the pattern of changes in the past years.

Keywords

Main Subjects

References

Acceleration of Joybari, Shaban (2003). “Using Satellite Data (Case Study: Khairud Educational Research Forest near Nowshahr), PhD Thesis”, University of Tehran, pp. 155. (in Persian)
Ahadi Nejad Rashti, Mohsen & Ahmad Hosseini (2011). “Assessing and Predicting Horizontal Change and Distribution of Cities Using Multi-Time Satellite Images and Geographic Information Systems Study study: Tabriz city in the period of 1363-1389) Urban research and planning, second year, fourth issue, pages. pp. 1-20. (in Persian)
Alavi panah, K. S. )2005(. Application remote sensing in earth science, published by University of Tehran, 45 pp.
Ali-Mohammadi Sarab, Abbas; Ali-Akbar Matkan; & Babak Mir-Bagheri (2010). Slvlh teacher performance assessment model Humanities - and Spatial Planning, fantails period, the second issue, Tehran. (in Persian)
Alimohammadi, A., Matkan, A., & Mirbagheri, B. (2010). “The Evaluation of CELLULAR AUTOMATA model efficiency in simulation of urban areas development (Case study: suburbs of south west of Tehran)”. J. Spat. Plan (Modares Human Sciences), 14: 2, pp. 81-102. (in Persian)
Arekhi, S. & M. Adibnejad (2011). “Efficiency assessment of the of Support Vector Machines for land use classification using Landsat ETM+ data (Case study: Ilam Dam Catchment)”, Iranian Journal of Range and Desert Reseach, 18 (3), pp. 420-440. (in Persian)
Arsanjani, J. J.; M. Helbich; W. Kainz; & A. D. Boloorani (2013). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. Int. J. Appl. Earth Obs. Geoinf, 21, pp. 265–275. (in Persian)
Asghari Zamani, Akbar; Saeed Maleki; Ali Movahedi (1389). (Predicting land use change in Zanjan using CLUE model), Geography and Situational Development, Vol. 8, No. 15, pp. 64-39. (in Persian)
Blaschke, T. (2009). “Object based image analysis for remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing”, journal homepage: www.elsevier.com/locate/isprsjprs. pp. 10-21.
Boniad, A. E. & Hajighaderi, T. (2008). “Mapping of Natural Forest Stands of Zanjan Province Using Landsat 7ETM+ sensor data”, Science and Technology of Agriculture and Natural Resources, (42) 11, pp. 627-638.
Dehvari, A. & Heck, R. J. (2009). “Comparison of object-based and pixel based infrared airborne image classification methods using DEM thematic layer”, Journal of Geography and Regional Planning, 2 (4), pp. 086-096.
Dongjie, G., HaiFeng, L., Takuro, I., Weici, S., Tadashi, N., & Kazunori, K. )2011(. “Modeling urban land use change by the integration of cellular automaton and Markov model”, Ecological Modeling, 222 (20), pp. 3761–3772.
Eastman, J. R. (2006). IDRISI Andes guide to GIS and image processing, Clark University, Worcester, 328 pp.
Faizizadeh, B. & Helali, H. (2009). Comparison of basic, object-oriented pixel method and effective parameters in land cover / land use classification of West Azerbaijan province, Natural Geographical Research, No. 71, pp. 73-84. (in Persian)
Fan, F., Weng, Q., & Wang, Y. (2007). Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery, Sensors, 7 (7), pp. 1323-1342.
Guan, D., Li, H., Inohae, T., Su, W., Nagaie, T., & Hokao, K. (2011). “Modeling urban land use change by the integration of cellular automaton and Markov model”, Ecological Modelling, 222(20-22), pp. 3761-3772.
Guan, D., Gao, W., Watari, K., & Fukahori, H. (2008). “Land use change of Kitakyushu based on landscape ecology and Markov model”, Journal of Geographical Sciences, 18 (4), pp. 455-468.
Hathout, S. (2002). “The use of GIS for monitoring and predicting urban growth in East and West St Paul, Winnipeg, Manitoba, Canada”, Journal of Environmental Management, 66 (3): pp. 229-238.
He, C. Y. et al (2008). “Modeling dynamic urban expansion processes incorporating a potential model with cellular automata”, Landscape Urban Plan, 86, pp. 79-91.
Houet, T. & Laurence, H. (2006). Modeling and projecting land-use and land-cover changes with Cellular Automaton in considering landscape trajectories, EARSeL eProceedings, 5, 1, United States.
Iqbal Sarwar Md. Billa M. Paul, Alak (2016). “Urban land use change analysis using RS and GIS in Sulakbahar ward in Chittagong city, Bangladesh”, Internatinal Journal Of Geomatics and geosciences,1, 7, pp. 1-10.
Kohonen, T. (2012). Self-organization and associative memory. Springer Science & BusinessMedia, 3 illustrated, pp. 312.
Liu, Y. Liu (2009). Modelling urban development with geographical information systems and cellular automata, CRC Press, 188 pp.
Mabudi, M. T. & Hakimi, H. (2016). “An analysis of land use land changes and simulation of urban expansion of middle-point cities (Case study: Khoy City)”, The Journal of Urban Planning Geography Research, 3 (2), pp. 211-226. (in Persian)
Matinfar, H. R., Sarmadian, F., & Alavi-Panah S. K., & Hech, R. J. (2007). Comparisons of Object-Oriented and Pixel-Based Classification of Land Use/Land Cover Types Based on Lansadsat7, Etm+ Spectral Bands (Case Study: Arid Region of Iran), American-Eurasian J. Agric. & Environ. Sci., 4 (4): pp. 448-456. (in Persian)
Munthali, M. G., Botai, J. O., Davis, N., & Adeola, A. M. (2019a). “Multitemporal analysis of land use and land cover changes detection for Dedza District of Malawi using geospatial techniques”, International Journal of Applied Engineering Research, 14 (5), pp. 1151–1162.
Nguyen, H. H., Dargusch, P., Moss, P., & Aziz, A. A. (2017). Land-use change and socio-ecological drivers of wetland conversion in Ha Tien Plain, Mekong Delta, Vietnam, Land Use Policy, 64, pp. 101-113.
Patino, J. E. & Duque Juan, C. (2013). “A review of regional science applications of satellite remote sensing in urban settings”, Computers, Environment and Urban Systems, Vol. 37, pp. 1-17. United Kingdom.
Piquer, R., Maria, T., Kuemmerle, D., Alcaraz, S., Raul, Zurita- M., & Javier, C. (2012). “Future land use effects on the connectivity of protected area networks in southeastern Spain”, Journal for Nature Conservation, 20 (6), pp. 326-336.
Pontius, R. G. & Chen, H. (2006). Geomod Modeling, USA: Clark University, pp. 44.
Rafieyan, O., Darvishsefat, A. A., Babaii, S., & Mataji, A. (2001). “Evaluation of pixel-based and object-based classification methods for tree identification using aerial images (Case study: a forestation in Chamestan-Nur)”, Iranian Journal of Forest, 3 (1), pp. 35-47. (in Persian)
Rasouli, A. A. (2008). Principles of remote sensing image processing applications, with emphasis on satellite, Tabriz University Press, 777 pp. (in Persian)
Rimal, B., Zhang, L., Keshtkar, H., Haack, B. N., Rijal, S., & Zhang, P. (2018). Land Use/Land Cover Dynamics and Modeling of Urban Land Expansion by the Integration of Cellular Automata and Markov Chain. ISPRS Int. J. Geo-Inf. 7 (4), 154 pp.
Rogan, J. & And, A. D. C. (2004). “Remote sensing technology for mapping and monitoring land cover And land use change”, Progress in Planning, 64, pp. 301-325.
Salmanmahini, A. & Kamyab, H. (2012). Applied Remote Sensing and GIS with Idrisi, 2nd Edition, Publication of Mehrmahdis, Tehran, Iran, 569 pp. (in Persian)
Sarah-Sokhteh, R. (2019). Using the program of evaluating the position and position of the user of new urban lands with the title of fast and high quality information from the center, geographic information model and remote sensing in the program, duration 10, number 4, winter 98, pp. 7-26. (in Persian)
Shojaeian, A., Mokhtari Chelcheleh, S., Keshtkar, L., & Soleimani, I. (2014). Using satellite imagery 8, Scientific-Research Quarterly Journal of Geographical Information. (in Persian)
Soe, Minit. Le Weng (2006). “Multicriteria decision approach for land use and land cover change using Markov chain analysis and a cellular automata approach”, Canadian Journal of Remote Sensing, pp. 32: 6, United Kingdom.
Soroudi, M. & Jozi, S. A. (2013). “Application of remote sensing and markov in investigation and prediction of change in vegetation cover (Case study: District 1 of Tehran Municipality)”, Journal of EnvironmentalStudies, 39, pp. 113-122. (in Persian)
Suriya, S. & Mudgal, B. (2012). “Impact of urbanization on flooding: The Thirusoolam sub watershed–A case study”, Journal ofHydrology, 412, pp. 210-219.
Traore, Arafan., Mawenda, John., Komba, Atupelye, W. (2018). Land-Cover Change Analysis and Simulation in Conakry (Guinea), Using Hybrid Cellular-Automata and Markov Model, Urban Sci. Vol. 2, Issue 2.
Judge Rahmati, Zero, Haidar Nejad, Nasim (2009). Physical expansion of cities and the need to determine Urban security Sample example: Isfahan city Geography and Environmental Observation, First Year, First issue, pp. 31-21. (in Persian)
Verburg, PH., Schot, PP., Dijst, MJ., & Veldkamp, A. (2004). “Land use change modelling: current practice and research priorities”, GeoJournal, 61 (4), pp. 309-324.
Zare Garizi, A., Sheikh, V., Sadoddin, A., & Mahiny, A. (2012). “Simulating the spatiotemporal changes of forest extent for the Chehelchay watershed (Golestan province), using integrated CA-Markov model”, Iranian Journal of Forest and Poplar Research, 20, pp. 273-285. (in Persian)
Ahadi-Nejad Ravshti, M. & Hosseini, A. (2011). Currency and Perspectives of Horizontal Changes and Distributions Eighteen (Case Study: The City of Tabriz in the Period 1363-1389) Urban Research and Planning, Second Year, No. 4, pp. 1-20. (in Persian)
Town and Country Planning
Volume 12, Issue 2
Autumn @ Winter
October 2020
Pages 407-430

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History

  • Receive Date: 19 April 2020
  • Revise Date: 21 June 2020
  • Accept Date: 21 June 2020

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